Development of an Algorithm for the Estimation of Contamination Sources in a Water Distribution Network

The complexity of a water distribution network (WDN) allows human imposition where accidental or intentional attack is possible. These attacks sometimes result in the contamination of water that has been treated at the treatment plant, and can eventually, be consumed by the society. However, the use of contaminated water has gross negative public health and socioeconomic implications on the society. Technically, being able to identify the source of contamination is particularly important for decision makers, so as to take immediate control strategies in order to minimize the consequences that can ensue from the use of contaminated water. There are two types of WDN analysis problem, which are: the steady state and the transient state conditions. In order to detect the continuous contamination that may be present in a WDN, this study considered a steady state condition. In this work, an approach for estimating the sources of contamination and the magnitude of concentration of the contaminant is proposed. Given a set of measurements, and by applying superposition technique, a model that embeds and relates the contaminant distribution to a set of given measurement in order to estimate the sources of contamination is formulated and, algorithm for solving it, is developed. The application of the proposed model is demonstrated on a water network with multiple injection contamination sources. The results of the estimated corresponding coefficient of determination for three cases are estimated (Case 1: 0.99894, Case 2: 0.99937 and Case 3 is 0.99974) while the corresponding root mean square were also obtained (Case 1: 0.000364, Case 2: 0.000351, Case 3: 0.000299) for a noise level of (5%). The same parameters were also obtained at a noise level of (10%). The obtained results verified the feasibility of the proposed novel approach, which can be applied to a larger water distribution network.